The importance of processing resolution in "ideal time-frequency segregation" of masked speech and the implications for predicting speech intelligibility.

Ideal time-frequency segregation (ITFS) is a signal processing technique that may be used to estimate the energetic and informational components of speech-on-speech masking. A core assumption of ITFS is that it roughly emulates the effects of energetic masking (EM) in a speech mixture. Thus, when speech identification thresholds are measured for ITFS-processed stimuli and compared to thresholds for unprocessed stimuli, the difference can be attributed to informational masking (IM). Interpreting this difference as a direct metric of IM, however, is complicated by the fine time-frequency (T-F) resolution typically used during ITFS, which may yield target "glimpses" that are too narrow/brief to be resolved by the ear in the mixture. Estimates of IM, therefore, may be inflated because the full effects of EM are not accounted for. Here, T-F resolution was varied during ITFS to determine if/how estimates of IM depend on processing resolution. Speech identification thresholds were measured for speech and noise maskers after ITFS. Reduced frequency resolution yielded poorer thresholds for both masker types. Reduced temporal resolution did so for noise maskers only. Results suggest that processing resolution strongly influences estimates of IM and implies that current approaches to predicting masked speech intelligibility should be modified to account for IM.